Joint production, transportation, and maintenance in downstream fuel supply chain

IF 1.7 4区 工程技术 Q3 ENGINEERING, INDUSTRIAL
Kamar Diaz, Mohamed Ali Kammoun, Zied Hajej, Naoufal Sefiani, Maria Francesca Milazzo
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引用次数: 0

Abstract

This paper presents an integrated production, maintenance, and transportation strategy for a multi-site, multi-demand, multi-tank fuel production system. Firstly, each site’s economic fuel production plan is developed under a random demand and service level. Then, a transportation plan is proposed to collaborate between sites in case of unavailability site or unmet needs, minimizing the total cost. According to the correlation between production and maintenance, a periodically preventive maintenance strategy is developed for both refining machines and storage tanks, while minimizing the incurred costs by considering the influence of fuel production rate on their failure rates. Additionally, in this study, experimental tests are performed on an industrial tank, based on the real-life case of fuel companies, to investigate the tanks’ degradation due to corrosion phenomena. The resolution complexity of the analytical model arises from its stochastic nature due to random demands. Hence, a transformation to a deterministic form is performed. Numerical examples and a sensitivity study are presented to illustrate the effectiveness of the proposed methodology and the obtained results.
下游燃料供应链中的联合生产、运输和维护
本文介绍了多站点、多需求、多油箱燃料生产系统的综合生产、维护和运输策略。首先,在随机需求和服务水平下,制定每个站点的经济燃料生产计划。然后,提出一个运输计划,以便在没有可用站点或需求未得到满足的情况下在站点之间进行协作,最大限度地降低总成本。根据生产和维护之间的相关性,为精炼设备和储油罐制定了定期预防性维护策略,同时考虑到燃料生产率对其故障率的影响,最大限度地降低了产生的成本。此外,本研究还根据燃料公司的实际情况,对工业储罐进行了实验测试,以研究储罐因腐蚀现象而导致的退化。分析模型的解析复杂性源于随机需求导致的随机性。因此,需要将其转换为确定性形式。为说明所建议方法的有效性和所获得的结果,介绍了数值示例和敏感性研究。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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来源期刊
CiteScore
4.50
自引率
19.00%
发文量
81
审稿时长
6-12 weeks
期刊介绍: The Journal of Risk and Reliability is for researchers and practitioners who are involved in the field of risk analysis and reliability engineering. The remit of the Journal covers concepts, theories, principles, approaches, methods and models for the proper understanding, assessment, characterisation and management of the risk and reliability of engineering systems. The journal welcomes papers which are based on mathematical and probabilistic analysis, simulation and/or optimisation, as well as works highlighting conceptual and managerial issues. Papers that provide perspectives on current practices and methods, and how to improve these, are also welcome
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